{"id":"https://openalex.org/W4388188697","doi":"https://doi.org/10.1145/3581783.3612495","title":"Counterfactual Cross-modality Reasoning for Weakly Supervised Video Moment Localization","display_name":"Counterfactual Cross-modality Reasoning for Weakly Supervised Video Moment Localization","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4388188697","doi":"https://doi.org/10.1145/3581783.3612495"},"language":"en","primary_location":{"id":"doi:10.1145/3581783.3612495","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3612495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075968933","display_name":"Zezhong Lv","orcid":"https://orcid.org/0000-0003-0207-8998"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zezhong Lv","raw_affiliation_strings":["Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0207-8998","affiliations":[{"raw_affiliation_string":"Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027552992","display_name":"Bing Su","orcid":"https://orcid.org/0000-0001-8560-1910"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Su","raw_affiliation_strings":["Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8560-1910","affiliations":[{"raw_affiliation_string":"Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025631695","display_name":"Ji-Rong Wen","orcid":"https://orcid.org/0000-0002-9777-9676"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji-Rong Wen","raw_affiliation_strings":["Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9777-9676","affiliations":[{"raw_affiliation_string":"Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5075968933"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":2.3549,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.90720681,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"6539","last_page":"6547"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.8432801365852356},{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.7946982383728027},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7684056162834167},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.7038477659225464},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6211437582969666},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.47240298986434937},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.41989603638648987},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4145641326904297},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37430477142333984},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3549949526786804},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12982681393623352}],"concepts":[{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.8432801365852356},{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.7946982383728027},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7684056162834167},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.7038477659225464},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6211437582969666},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.47240298986434937},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.41989603638648987},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4145641326904297},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37430477142333984},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3549949526786804},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12982681393623352},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3581783.3612495","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3612495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2953121989","display_name":null,"funder_award_id":"No. 61976206, No. 61832017","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1927052826","https://openalex.org/W2337252826","https://openalex.org/W2486285194","https://openalex.org/W2597958930","https://openalex.org/W2962876901","https://openalex.org/W2963017553","https://openalex.org/W2964089981","https://openalex.org/W2979933490","https://openalex.org/W2997429269","https://openalex.org/W2998355566","https://openalex.org/W2999905431","https://openalex.org/W3034743747","https://openalex.org/W3093051565","https://openalex.org/W3093471110","https://openalex.org/W3103542727","https://openalex.org/W3118778629","https://openalex.org/W3130619535","https://openalex.org/W3172048555","https://openalex.org/W3176201273","https://openalex.org/W3176444885","https://openalex.org/W3177934633","https://openalex.org/W3178322352","https://openalex.org/W3186567887","https://openalex.org/W3202168743","https://openalex.org/W3210101297","https://openalex.org/W4230025115","https://openalex.org/W4283814553","https://openalex.org/W4298364821","https://openalex.org/W4312402470"],"related_works":["https://openalex.org/W3201448254","https://openalex.org/W4286970243","https://openalex.org/W2066431708","https://openalex.org/W3113091479","https://openalex.org/W4384133558","https://openalex.org/W2162899405","https://openalex.org/W3025615835","https://openalex.org/W173210993","https://openalex.org/W2390660599","https://openalex.org/W4284706735"],"abstract_inverted_index":{"Video":[0],"moment":[1],"localization":[2],"aims":[3],"to":[4,14,182,205],"retrieve":[5],"the":[6,15,26,31,41,46,53,56,62,68,74,89,95,100,103,108,114,120,128,174,178,183,191,200,214],"target":[7,32],"segment":[8,33],"of":[9,30,40,116,160,177,194,202,216],"an":[10,156],"untrimmed":[11],"video":[12,57,86,203],"according":[13],"natural":[16],"language":[17,59],"query.":[18],"Weakly":[19],"supervised":[20,48],"methods":[21],"gains":[22],"attention":[23],"recently,":[24],"as":[25,155],"precise":[27],"temporal":[28,64],"location":[29],"is":[34,50,185,222],"not":[35,124],"always":[36],"available.":[37],"However,":[38,88],"one":[39],"greatest":[42],"challenges":[43],"encountered":[44],"by":[45,61,78,94,166,189],"weakly":[47],"method":[49],"implied":[51],"in":[52],"mismatch":[54],"between":[55,82,99],"and":[58,84,102,111,136,162],"induced":[60],"coarse":[63],"annotations.":[65],"To":[66],"refine":[67],"vision-language":[69],"alignment,":[70],"recent":[71],"works":[72],"contrast":[73],"cross-modality":[75,129,146,161,169],"similarities":[76],"driven":[77],"reconstructing":[79],"masked":[80,104,121,195],"queries":[81],"positive":[83],"negative":[85],"proposals.":[87],"reconstruction":[90,154,184],"may":[91],"be":[92],"influenced":[93],"latent":[96],"spurious":[97,139,175],"correlation":[98,140],"unmasked":[101,179],"parts,":[105],"which":[106],"distorts":[107],"restoring":[109],"process":[110],"further":[112],"degrades":[113],"efficacy":[115],"contrastive":[117,208],"learning":[118],"since":[119],"words":[122],"are":[123],"completely":[125],"reconstructed":[126],"from":[127],"knowledge.":[130,164],"In":[131],"this":[132,138,172],"paper,":[133],"we":[134,150,197],"discover":[135],"mitigate":[137],"through":[141],"a":[142],"novel":[143],"proposed":[144,218],"counterfactual":[145,168],"reasoning":[147],"method.":[148,219],"Specifically,":[149],"first":[151],"formulate":[152],"query":[153,163],"aggregated":[157],"causal":[158],"effect":[159,193],"Then":[165],"introducing":[167],"knowledge":[170],"into":[171],"aggregation,":[173],"impact":[176],"part":[180],"contributing":[181],"explicitly":[186],"modeled.":[187],"Finally,":[188],"suppressing":[190],"unimodal":[192],"query,":[196],"can":[198],"rectify":[199],"reconstructions":[201],"proposals":[204],"perform":[206],"reasonable":[207],"learning.":[209],"Extensive":[210],"experimental":[211],"evaluations":[212],"demonstrate":[213],"effectiveness":[215],"our":[217],"The":[220],"code":[221],"available":[223],"at":[224],"https://github.com/sLdZ0306/CCR":[225],"https://github.com/sLdZ0306/CCR.":[226]},"counts_by_year":[{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}